Text Classification
Transformers
TensorBoard
Safetensors
bert
HHD
10_class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use dbcheesetoast/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbcheesetoast/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dbcheesetoast/model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dbcheesetoast/model_output") model = AutoModelForSequenceClassification.from_pretrained("dbcheesetoast/model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 508766505bbe7ae8d776623b0d8f6c9c505a8edd89d793eda958609014b0fe5e
- Size of remote file:
- 5.18 kB
- SHA256:
- 354ee1dac572111c6601c1e3b953e70a2be582ba59600a6abd08f4df45b805a0
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